๐๐ฟ๐ผ๐บ ๐ฃ๐ฒ๐ฟ๐ฐ๐ฒ๐ฝ๐๐ฟ๐ผ๐ป ๐๐ผ ๐ ๐๐ฃ: ๐๐ฑ๐๐ฎ๐ป๐ฐ๐ถ๐ป๐ด ๐๐ฒ๐๐ผ๐ป๐ฑ ๐๐ผ๐ด๐ถ๐๐๐ถ๐ฐ ๐ฅ๐ฒ๐ด๐ฟ๐ฒ๐๐๐ถ๐ผ๐ป
In one of my previous animations, I demonstrated how the ๐น๐ผ๐ด๐ถ๐๐๐ถ๐ฐ ๐ฟ๐ฒ๐ด๐ฟ๐ฒ๐๐๐ถ๐ผ๐ป ๐ฎ๐น๐ด๐ผ๐ฟ๐ถ๐๐ต๐บ can outperform the ๐ฝ๐ฒ๐ฟ๐ฐ๐ฒ๐ฝ๐๐ฟ๐ผ๐ป ๐ฎ๐น๐ด๐ผ๐ฟ๐ถ๐๐ต๐บ by leveraging the logistic (sigmoid) function to calculate maximum likelihood. In contrast, the perceptron relies on a simple ๐๐๐ฒ๐ฝ ๐ณ๐๐ป๐ฐ๐๐ถ๐ผ๐ป as its activation function.
However, modifying the perceptron algorithm unlocks vast possibilitiesโpaving the way for neural networks. This evolved version, known as the ๐ ๐๐น๐๐ถ๐น๐ฎ๐๐ฒ๐ฟ ๐ฃ๐ฒ๐ฟ๐ฐ๐ฒ๐ฝ๐๐ฟ๐ผ๐ป (๐ ๐๐ฃ) ๐๐น๐ฎ๐๐๐ถ๐ณ๐ถ๐ฒ๐ฟ, supports multiple activation functions, allowing it to classify ๐ป๐ผ๐ป-๐น๐ถ๐ป๐ฒ๐ฎ๐ฟ๐น๐ ๐๐ฒ๐ฝ๐ฎ๐ฟ๐ฎ๐ฏ๐น๐ฒ ๐ฑ๐ฎ๐๐ฎโa key limitation of logistic regression.
To deepen your understanding, I highly recommend exploring these insightful video explanations:
๐๐ผ๐ด๐ถ๐๐๐ถ๐ฐ ๐ฅ๐ฒ๐ด๐ฟ๐ฒ๐๐๐ถ๐ผ๐ป: by Pritam Kudale
โถ๏ธ ๐๐ผ๐ด๐ถ๐๐๐ถ๐ฐ ๐ฅ๐ฒ๐ด๐ฟ๐ฒ๐๐๐ถ๐ผ๐ป ๐ฆ๐ถ๐บ๐ฝ๐น๐ถ๐ณ๐ถ๐ฒ๐ฑ
โถ๏ธ ๐๐ผ๐๐ ๐๐๐ป๐ฐ๐๐ถ๐ผ๐ป & ๐ก๐ฒ๐ด๐ฎ๐๐ถ๐๐ฒ ๐๐ผ๐ด ๐๐ถ๐ธ๐ฒ๐น๐ถ๐ต๐ผ๐ผ๐ฑ
โถ๏ธ ๐๐ฟ๐ฎ๐ฑ๐ถ๐ฒ๐ป๐ ๐๐ฒ๐๐ฐ๐ฒ๐ป๐ & ๐๐ผ๐บ๐ฝ๐น๐ฒ๐๐ฒ ๐๐ฒ๐ฟ๐ถ๐๐ฎ๐๐ถ๐ผ๐ป
๐ฃ๐ฒ๐ฟ๐ฐ๐ฒ๐ฝ๐๐ฟ๐ผ๐ป ๐๐น๐ด๐ผ๐ฟ๐ถ๐๐ต๐บ:
โถ๏ธ ๐ฃ๐ฒ๐ฟ๐ฐ๐ฒ๐ฝ๐๐ฟ๐ผ๐ป ๐๐น๐ด๐ผ๐ฟ๐ถ๐๐ต๐บ: The First Step Towards Logistic Regression
For more AI and machine learning insights, explore Vizuraโs AI Newsletter:
#MachineLearning #AI #DeepLearning #LogisticRegression #Perceptron #MLP #NeuralNetworks #DataScience